A Study of Chinese Medicine Consultation Strategies Based on Frequent Pattern Mining Algorithms
Objective To study Chinese medicine consultation strategies to achieve rapid capture of key information about patients'conditions and to advance the development of objectification in Chinese medicine consultation.Methods A symptom questioning model based on frequent pattern mining algorithm in correlation analysis was used,and a cross-merging method was used to establish a TCM symptom questioning strategy between single-system symptom questioning and multi-system integrated symptom questioning in TCM,to achieve the shortest time and highest efficiency in capturing key information about the patient's condition.Results A breakthrough from single-system questioning to five-system integrated questioning was achieved,and the process of efficiently obtaining information about the patient's condition was achieved through both single-system and five-system symptom questioning modes,and the system was able to obtain 92%of the patient's symptom information with at most 65%fewer questions than the traditional scale questioning method,greatly improving the efficiency of obtaining information about the patient's symptoms.Conclusion With the two different symptom questioning modes,the traditional TCM questioning mode of asking patients based on scales is broken,the time to obtain symptoms from patients is shortened,the questioning process is simplified,and discrepancies due to inexperience or human subjectivity are reduced,which can be used in clinical aids to diagnosis in TCM.
Chinese medicine consultationFrequent pattern mining algorithmSymptom correlationConsultation strategy
NETL
NSTL
万方数据
